SynthesisBMC neurology2023
Neuroimaging and machine learning for studying the pathways from mild cognitive impairment to alzheimer's disease: a systematic review.
Synthesis in BMC neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Scalable CT-based prognostic modeling of dementia conversion in mild cognitive impairment.Scientific reports · 2026Article
- Prediction of alzheimer's disease time to dementia onset using cross-sectional data from spatiotemporal biomarker progression patterns.European journal of nuclear medicine and molecular imaging · 2026Article
- Ultra-fast MRI for brain-age prediction in a real-world cognitive disorders clinic.Frontiers in aging neuroscience · 2026Article
- Multimodal neuroimaging and AI integration in cognitive disorders: advances, challenges, and future directions for precision medicine.Psychoradiology · 2026Review
- Vision and convolutional transformers for Alzheimer's disease diagnosis: a systematic review of architectures, multimodal fusion and critical gaps.Brain informatics · 2025Review
- Development and Validation of a Brain Aging Biomarker in Middle-Aged and Older Adults: Deep Learning Approach.JMIR aging · 2025Article
- Detection of emergency department patients at risk of dementia through artificial intelligence.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Observational
- Neurotechnological Approaches to Cognitive Rehabilitation in Mild Cognitive Impairment: A Systematic Review of Neuromodulation, EEG, Virtual Reality, and Emerging AI Applications.Brain sciences · 2025Review
- Longitudinal Analysis of Amyloid PET and Brain MRI for Predicting Conversion from Mild Cognitive Impairment to Alzheimer's Disease: Findings from the ADNI Cohort.Tomography (Ann Arbor, Mich.) · 2025Article
- Research on interpretable machine learning models for diagnosis and staging of mild cognitive impairment.Frontiers in neurology · 2025Article
- Multivariate Modelling and Prediction of High-Frequency Sensor-Based Cerebral Physiologic Signals: Narrative Review of Machine Learning Methodologies.Sensors (Basel, Switzerland) · 2024Review
- Embracing Older Adults' Perspectives: Enhancing Models of Successful Ageing.International dental journal · 2024Article
- Management of MCI in the Outpatient Setting.Current psychiatry reports · 2024Review
- How does the precise prediction of preeclampsia onset aid the overall management of preeclampsia?Hypertension research : official journal of the Japanese Society of Hypertension · 2024Article
- Positive Effect of Super-Resolved Structural Magnetic Resonance Imaging for Mild Cognitive Impairment Detection.Brain sciences · 2024Article
- Multi-modal machine learning and gut microbiome pathway analysis for Alzheimer's risk prediction.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis systematic review synthesizes the most recent neuroimaging procedures and machine learning approaches for the prediction of conversion from mild cognitive impairment to Alzheimer's disease dementia.
methodsWe systematically searched PubMed, SCOPUS, and Web of Science databases following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) systematic review guidelines.
resultsOur search returned 2572 articles, 56 of which met the criteria for inclusion in the final selection. The multimodality framework and deep learning techniques showed potential for predicting the conversion of MCI to AD dementia.
conclusionFindings of this systematic review identified that the possibility of using neuroimaging data processed by advanced learning algorithms is promising for the prediction of AD progression. We also provided a detailed description of the challenges that researchers are faced along with future research directions. The protocol has been registered in the International Prospective Register of Systematic Reviews- CRD42019133402 and published in the Systematic Reviews journal.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.